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The Drift-Diffusion Model (DDM) is widely used in neuropsychological studies to understand the decision process by incorporating both reaction times and subjects' responses. Various models have been developed to estimate DDM parameters,…

Applications · Statistics 2025-07-03 Zekai Jin , Yaakov Stern , Seonjoo Lee

Self-diffusion coefficients, $D^*$, are routinely estimated from molecular dynamics simulations by fitting a linear model to the observed mean-squared displacements (MSDs) of mobile species. MSDs derived from simulation exhibit statistical…

Statistical Mechanics · Physics 2026-01-05 Andrew R. McCluskey , Samuel W. Coles , Benjamin J. Morgan

The Wigner spacing distribution has a long and illustrious history in nuclear physics and in the quantum mechanics of classically chaotic systems. In this paper, a novel connection between the Wigner distribution and 2D classical mechanics…

Chaotic Dynamics · Physics 2017-08-03 Jamal Sakhr

We develop a comprehensive analysis of the Kirkwood-Dirac distributions in classical optics, revealing their deep connection with optical coherence as fundamental concept in optics. From their very definition, the Kirkwood-Dirac…

Quantum Physics · Physics 2026-04-10 Alfredo Luis , Lorena Ballesteros Ferraz

Functionals in geometric probability are often expressed as sums of bounded functions exhibiting exponential stabilization. Methods based on cumulant techniques and exponential modifications of measures show that such functionals satisfy…

Probability · Mathematics 2009-09-29 Yu Baryshnikov , P. Eichelsbacher , T. Schreiber , J. E. Yukich

Rademacher theorem states that every Lipschitz function on the Euclidean space is differentiable almost everywhere, where "almost everywhere" refers to the Lebesgue measure. In this paper we prove a differentiability result of similar type,…

Classical Analysis and ODEs · Mathematics 2015-03-27 Giovanni Alberti , Andrea Marchese

The distribution function of a random distance in three dimensions is given and some new three-dimensional d2-tests of randomness are suggested. We show that our test statistics are not correlated with the usual test statistics and are…

Applications · Statistics 2014-02-24 Sergii Koliada

The distance standard deviation, which arises in distance correlation analysis of multivariate data, is studied as a measure of spread. The asymptotic distribution of the empirical distance standard deviation is derived under the assumption…

Statistics Theory · Mathematics 2019-12-12 Dominic Edelmann , Donald Richards , Daniel Vogel

We study a symmetric random walk (RW) in one spatial dimension in environment, formed by several zones of finite width, where the probability of transition between two neighboring points and corresponding diffusion coefficient are…

Statistical Mechanics · Physics 2017-04-03 A. V. Nazarenko , V. Blavatska

A large variety of problems in statistical physics use a Gaussian distribution as a starting point. For the problem of intermittency in fluid turbulence, the Gaussian approximation is not a useful beginning. We find that the Cramer's rate…

Statistical Mechanics · Physics 2008-11-04 Jayanta Kumar Bhattacharjee , Sagar Chakraborty , Arnab Saha

Symmetry is a cornerstone of much of mathematics, and many probability distributions possess symmetries characterized by their invariance to a collection of group actions. Thus, many mathematical and statistical methods rely on such…

Statistics Theory · Mathematics 2023-10-23 Adam B Kashlak

A cyclic random motion at finite velocity with orthogonal directions is considered in the plane and in $\mathbb{R}^3$. We obtain in both cases the explicit conditional distributions of the position of the moving particle when the number of…

Probability · Mathematics 2020-01-01 E. Orsingher , R. Garra , A. I. Zeifman

We present new connections among anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem. This is done by defining a point transformation to a new position variable, which we postulate to be Cartesian, motivated by…

Mathematical Physics · Physics 2018-01-08 Donald J. Kouri , Nikhil N. Pandya , Cameron L. Williams , Bernhard G. Bodmann , Jie Yao

A new method is presented for assigning distributional curvature, in an invariant manner, to a space-time of low differentiability, using the techniques of Colombeau's `new generalised functions'. The method is applied to show that…

General Relativity and Quantum Cosmology · Physics 2009-10-28 C J S Clarke , J A Vickers , J P Wilson

A Walsh diffusion on Euclidean space moves along each ray from the origin, as a solution to a stochastic differential equation with certain drift and diffusion coefficients, as long as it stays away from the origin. As it hits the origin,…

Probability · Mathematics 2018-07-02 Tomoyuki Ichiba , Andrey Sarantsev

We consider random walks in a random environment that is given by i.i.d. Dirichlet distributions at each vertex of Z^d or, equivalently, oriented edge reinforced random walks on Z^d. The parameters of the distribution are a 2d-uplet of…

Probability · Mathematics 2013-09-20 Christophe Sabot , Laurent Tournier

A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be…

Methodology · Statistics 2018-03-01 Rose Baker

The effective equations of motion for a point charged particle taking account of radiation reaction are considered in various space-time dimensions. The divergencies steaming from the pointness of the particle are studied and the effective…

High Energy Physics - Theory · Physics 2009-11-07 P. O. Kazinski , S. L. Lyakhovich , A. A. Sharapov

We speculate on the role of relativistic versions of delayed differential equations in fundamental physics. Relativistic invariance implies that we must consider both advanced and retarded terms in the equations, so we refer to them as…

High Energy Physics - Theory · Physics 2010-09-17 Michael Atiyah , Gregory W. Moore

Because the stochastic calculus yields rarely random variables with laws defined by explicit closed formulas, probabilistic numerical computations are done most often by simulation. The simulation by the shift, whose field of application is…

Probability · Mathematics 2007-05-23 Nicolas Bouleau